Abstract：
Hundreds of genes are proposed to contribute to nociception and pain perception. Historically, most studies of pain-related genes have examined them in isolation or alongside a handful of other genes. More recently the use of systems biology techniques has enabled us to study genes in the context of the biological pathways and networks in which they operate. Here we describe a Web-based resource, available at http://www.PainNetworks.org. It integrates interaction data from various public databases with information on known pain genes taken from several sources (eg, The Pain Genes Database) and allows the user to examine a gene (or set of genes) of interest alongside known interaction partners. This information is displayed by the resource in the form of a network. The user can enrich these networks by using data from pain-focused gene expression studies to highlight genes that change expression in a given experiment or pairs of genes showing correlated expression patterns across different experiments. Genes in the networks are annotated in several ways including biological function and drug binding. The Web site can be used to find out more about a gene of interest by looking at the function of its interaction partners. It can also be used to interpret the results of a functional genomics experiment by revealing putative novel pain-related genes that have similar expression patterns to known pain-related genes and by ranking genes according to their network connections with known pain genes. We expect this resource to grow over time and become a valuable asset to the pain community.
摘要：
数百种基因被认为有助于伤害感受和疼痛感知。历史上,大多数关于疼痛相关基因的研究都单独或与少数其他基因一起检查了它们。最近，系统生物学技术的使用使我们能够在其运作的生物途径和网络的背景下研究基因。在这里，我们描述一个基于Web的资源，可在http://www上获得。PainNetworks.org.它将来自各种公共数据库的交互数据与来自多个来源的已知疼痛基因的信息（例如，疼痛基因数据库），并允许用户与已知的相互作用伙伴一起检查感兴趣的基因（或一组基因）。该信息由资源以网络的形式显示。用户可以通过使用来自疼痛集中基因表达研究的数据来丰富这些网络，以突出显示在给定实验中改变表达的基因或在不同实验中显示相关表达模式的基因对。网络中的基因以几种方式进行注释，包括生物学功能和药物结合。通过查看其相互作用伙伴的功能，该网站可用于了解有关感兴趣基因的更多信息。它还可以通过揭示与已知疼痛相关基因具有相似表达模式的推定的新型疼痛相关基因，并根据其与已知疼痛基因的网络连接对基因进行排名，来解释功能基因组学实验的结果。我们希望这种资源随着时间的推移而增长，并成为疼痛社区的宝贵资产。
